|Year : 2018 | Volume
| Issue : 3 | Page : 91-101
Prioritizing factors affecting the hospital employees' productivity from the hospital managers' viewpoint using integrated decision-making trial and evaluation laboratory and analytic network process
Ardalan Feili1, Amir Khodadad2, Ramin Ravangard3
1 Faculty of Economic and Administrative Sciences, Department of Management, Ferdowsi University of Mashhad, Mashhad, Iran
2 Department of Health Services Management; Student Research Committee, School of Management and Medical Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
3 Student Research Committee; Health Human Resources Research Center, School of Management and Medical Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
|Date of Submission||20-Oct-2017|
|Date of Decision||02-Dec-2017|
|Date of Acceptance||22-Dec-2017|
|Date of Web Publication||1-Jun-2018|
Dr. Ramin Ravangard
Department of Health Services Management, School of Management and Medical Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran. Health Human Resource Research Center, School of Management and Medical Information Sciences, Shiraz University of Medical Sciences, Shiraz
Source of Support: None, Conflict of Interest: None
Objectives: This study aimed to identify and prioritize factors affecting the hospital employees' productivity from the viewpoint of hospital managers working in the teaching hospitals affiliated to Iran, Shiraz University of Medical Sciences, in 2017. Materials and Methods: This was an applied, cross-sectional, and descriptive-analytical study conducted in 2017 in all teaching hospitals affiliated to Iran, Shiraz University of Medical Sciences. After identifying factors affecting hospital employees' productivity using the results of previous studies, all hospital managers (56 managers) were selected as the study population using census method to prioritize the factors. The decision-making trial and evaluation laboratory (DEMATEL) and analytic network process (ANP) techniques were used for analyzing the collected data through Excel 2010 and Super Decision 2.8. Results: Fifteen factors affecting employees' productivity were determined using the results of previous studies which were classified into four clusters. The results of DEMATEL technique showed that “employees' attitude toward the organization” was the most affecting factor (r = 11.928) and also the most affected factor (c = 12.120), as well as the most important factor affecting the employees' productivity (r + c = 24.048). In addition, the results of ANP showed that the cluster of “leadership and management styles” (relative weight [RW] = 0.274) and its factors, especially “involving employees in the decision-making processes” (L1) (RW = 0.102) and “delegation of authority to the employees” (L2) (RW = 0.100) were the most important factors affecting the employees' productivity. Conclusion: According to the results, adopting an appropriate leadership style and providing participatory management, involving the employees in the hospital decision-making processes, etc., had significant effects on the increases in the employees' motivation and productivity.
Keywords: Labor productivity, hospital managers, teaching hospitals, Iran
|How to cite this article:|
Feili A, Khodadad A, Ravangard R. Prioritizing factors affecting the hospital employees' productivity from the hospital managers' viewpoint using integrated decision-making trial and evaluation laboratory and analytic network process. J Med Sci 2018;38:91-101
|How to cite this URL:|
Feili A, Khodadad A, Ravangard R. Prioritizing factors affecting the hospital employees' productivity from the hospital managers' viewpoint using integrated decision-making trial and evaluation laboratory and analytic network process. J Med Sci [serial online] 2018 [cited 2018 Jun 22];38:91-101. Available from: http://www.jmedscindmc.com/text.asp?2018/38/3/91/229492
| Introduction|| |
In today's competitive world, increasing the productivity, as a philosophy based on the improvement strategy, is the most important goal of each organization, and is paid attention in the activities of all society sectors so that the main purpose of managers is the effective use of available resources, including workforce, money, materials, energy, and information. Improved productivity can enable organizations to increase their international competitiveness and growth, as well as their social cooperation. The low productivity indicates the waste of resources used by an organization which eventually leads to the loss of international competitiveness and whereby the reduced organizational business activities. In general, it can be said that a productive organization is an organization which can achieve its goals in less time and with minimal costs. On the other hand, because among the factors of production, the human resources, unlike other organizational resources, are known as sentient and the coordinator of other factors and also are the main levers to increase or decrease the organizational productivity, they have a special priority and should be paid particular attention. In other words, organizations which have made significant achievements and countries which have been among the advanced countries have put their emphasis on their human resources. Therefore, if the employees are motivated, capable, and productive, they can use other resources efficiently and productively and the aim of organizational productivity can be achieved. Otherwise, the stagnation and backwardness are the results of passive and unmotivated employees. Therefore, it can be concluded that labor productivity is the key factor affecting the overall productivity of production factors in organizations. Hence, first of all, the factors affecting labor productivity should be understood and then they should be effectively managed. In other words, trying to understand the concepts of productivity and trying to determine factors affecting it are one of the essential prerequisites for achieving the growth and development of the organization. Since the labor productivity is a function of many factors and their importance and effects on the labor productivity are not the same, it is not possible for organizations to take measures to improve all of them at the same time. Thus, for achieving the highest productivity, it is necessary to determine and prioritize the most important ones and then take some appropriate measures and develop required plans in order to improve the employees' productivity.
The results of various studies in this area have shown that factors such as the leadership and management styles;,,, individual factors;,,,,, positive attitude toward the job and organization; organizational culture; organizational structure;,, factors related to the organizational support; employees' compensation system; reward and incentive systems;,,, holding the training courses;,,, physical, psychological, and environmental factors;,, hospital technology and equipment; employees' motivation and job satisfaction; factors related to the job and the employees' freedom and independence at work;,,,, job stress; the existence of an atmosphere of cordiality and cooperation in the hospital;, factors related to the employees' sense of commitment and loyalty; teamwork, cooperation, and communication among team members with each other and with the managers; and perceived organizational justice  have effects on the employees' productivity in the organizations.
On the other hand, nowadays, the increased productivity and optimal use of limited resources and making accurate assessment of the quality of services provided are the most important objectives of hospitals and health-care centers in order to maintain and promote people's health, increase their satisfaction, and meet their expectations. In other words, the hospital managers can pave their way for achieving organizational goals and improve the country's development in the health sector through increasing the hospital productivity. However, unlike the industrial and commercial organizations, the health-care organizations, especially in Iran, have rarely studied ways to increase their employees' productivity. In other words, they have usually focused on only measuring the administrative productivity. In the present study, factors affecting the hospital employees' productivity were determined according to the literature review and results of previous studies, and then were prioritized from the viewpoint of managers working in the teaching hospitals affiliated to Iran, Shiraz University of Medical Sciences, in 2017.
| Materials and Methods|| |
This was an applied, cross-sectional, and descriptive-analytical study conducted in 2017 in all teaching hospitals affiliated to Iran, Shiraz University of Medical Sciences (14 hospitals). Since the human resource productivity is an issue in the field of management, the study population and experts were determined from the managers who had at least 5 years of work experience in the managerial positions and had sufficient knowledge of and familiarity with the hospital environment and the employees' capabilities. Therefore, all hospitals' chief executive officers, nursing managers and matrons, and administrative–financial managers (56 managers) were studied using census method. The managers were authorized to participate in the present study and entered the study after giving informed consent and all of them were assured of the confidentiality of their responses. The process of collecting required data was as follows:
First, factors affecting employees' productivity were identified using the results of previous studies and literature review.,,,,,,,, Then, for determining the impacts of each factor on the other studied factors and prioritizing them, two researcher-made questionnaires were used to collect the data. To gather the studied experts' viewpoints on the impact of each identified factor on the employees' productivity, a Decision-Making Trial and Evaluation Laboratory (DEMATEL) questionnaire was used. The data analysis using the DEMATEL technique led to drawing a network relation map (NRM). At the next phase and using this map, the network of factors affecting employees' productivity was developed, and to prioritize the factors using analytic network process (ANP), a pairwise comparison questionnaire was used. In addition, the degree of inconsistency was checked for each set of experts' judgments and each related matrix using inconsistency ratio. The inconsistency ratio of about 10% or less can be considered acceptable, and if the ratio is more than 10%, the subjective judgments need revisions. To analyze the collected data, Excel 2010 and Super Decision 2.8 (www.creativedecisions.org) were used. Different steps of techniques used in the present study, i.e., DEMATEL and ANP, have been described below.
The Decision-Making Trial and Evaluation Laboratory technique
DEMATEL technique was introduced for the first time in 1971 by Geneva Battelle Institute and was used to solve the technological and human issues, including race, hunger, environmental protection, and other problems. This technique provides a comprehensive method based on the graph theory and makes it possible to visually analyze the issues and structural models. As diagraphs (directed graphs) can better show the relationships between the elements of a system, this technique is based on graphs and can divide the influential factors into two groups of cause and effect and show the relationship among them in an understandable structural model. In general, the steps of applying DEMATEL technique are as follows:
- Identifying factors that may affect the employees' productivity through previous results and literature review
- Identifying the relationships among these factors using a pairwise comparison questionnaire completed by the studied managers and experts and calculating the average matrix (A) or initial direct relation matrix. The comparisons between each of the two factors located in a row and a column of the pairwise comparison questionnaire (aij) are made to represent the degree of influence of one element on another in which 0 = “No influence,” 1 = “Low influence,” 2 = “Medium influence,” 3 = “High influence,” and 4= “Very high influence”
- Determining the hierarchy of factors through sum of the i th row of the matrix T (ri), sum of the j th column (cj), (ri+ cj), and (ri− cj) using the following equation:
- It should be noted that ri indicates the total effects, both direct and indirect, which are given by the factor i to other factors, and cj denotes the total effects, both direct and indirect, received by the factor j from other factors. When j = i, ri+ cj represents the total effects both given and received by the factor i. In other words, it indicates the amount of interaction which i has with other factors, and the higher its amount is, the stronger its interaction and the higher its importance in the entire system. Also, ri− cj shows the net effect that the factor i contributes to the system. When ri− cj is positive, the factor i is the net cause, and if ri− cj is negative, the factor i is a net effect
- Determining a threshold value to obtain the digraph by computing the average of the elements in the Matrix T
- Drawing a NRM which is constructed by mapping all coordinate sets of (ri+ cj) and (ri− cj) to show the complex interrelationships. This diagram provides information about which factor has the most important effect and which one is the most important cause.,,
The analytic network process
ANP, developed by Saaty and an extension of analytic hierarchy process, represents a decision-making problem or a complex setting as a network of elements, including criteria and other alternatives, which are grouped into clusters. A network can incorporate feedback and complex interrelationships within and between clusters. ANP can deal with both quantitative and qualitative elements and factors under multiple criteria. In ANP, pairwise comparisons are used for determining the relative importance or strength of the impacts on a studied element, and the interdependencies within the levels of clusters, and reciprocally dependent elements in a cluster are evaluated. In general, the steps of applying ANP are as follows:
- Determining the relationships among studied elements and clusters and developing a model
- Determining the relative importance weights of elements using the pairwise comparisons with a scale of 1 (equal importance) to 9 (extreme importance), as well as calculating the inconsistency ratio
- Forming the unweighted supermatrix which contains the priorities of the elements derived from the pairwise comparisons throughout the network
- Forming the weighted matrix which is obtained by multiplying all the elements in a component of the unweighted supermatrix by the corresponding cluster weight
- Forming the limit supermatrix which is obtained by raising the weighted supermatrix to powers by multiplying it times itself. When the column of numbers is the same for every column, the limit matrix has been reached and the matrix multiplication process is stopped
- Identifying the final priorities of the elements and alternatives based on the limit supermatrix and selecting the best element and alternative which is that with the highest priority.,,
| Results|| |
First, 15 factors affecting the hospital employees' productivity were determined using the previous studies and literature review which were classified into four clusters of job and motivational factors, leadership and management styles, personal factors, and environmental factors [Table 1]. The structural model of factors affecting employees' productivity has been presented in [Figure 1], indicating the inner and outer dependencies.
|Table 1: Factors affecting the hospital employees' productivity using the previous studies and literature review|
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|Figure 1: The structural model of studied factors affecting the hospital employees' productivity|
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To identify the causal relationships between factors affecting employees' productivity, the DEMATEL technique was used and the studied managers' viewpoints were taken using the pairwise comparison questionnaire and the average matrix (A) was calculated. It should be noted that, in the present study, the inconsistency ratio of each matrix was <0.1 and therefore, was acceptable [Table 2].
Then, to calculate the normalized average matrix or initial direct relation matrix (D), each of the average matrix elements was multiplied by the inverse of 27.102 (the highest sum of rows) [Table 3].
|Table 3: The normalized average matrix or initial direct relation matrix (D) of the studied managers' viewpoints|
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Next, the total relation matrix (T) was computed using the equation T = S (I − S)−1 [Table 4]. The results of analyzing this matrix have been presented in [Table 5], which summarizes the direct and indirect effects of studied factors. This table indicates that “employees' attitude toward the organization” was the most affecting factor (r = 11.928) and also the most affected factor (c = 12.120) among all the studied factors. Moreover, this factor was the most important factor affecting the employees' productivity (r + c = 24.048).
|Table 4: The total relation matrix (T) of the studied managers' viewpoints|
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|Table 5: The sum of influences given and received among the studied factors|
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In the next step, the threshold value was determined as 0.732 by computing the average of the elements in the matrix T. Therefore, the elements whose values were greater than the threshold value were considered as the elements and factors affecting the employees' productivity in the DEMATEL NRM. In this map, the effects of all factors affecting the employees' productivity on each other have been shown [Figure 2].
|Figure 2: The network relation map of factors affecting the hospital employees' productivity from the studied managers' viewpoints|
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In the next phase of the study, the unweighted supermatrix [Table 6] using the DEMATEL Matrix T and NRM, weighted supermatrix [Table 7] and limit supermatrix [Table 8] were calculated using the ANP technique and the studied managers' pairwise comparisons among factors affecting the employees' productivity and therefore, the final priorities of the factors were identified.
|Table 6: The unweighted supermatrix of factors affecting the employees' productivity from the studied managers' viewpoints|
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|Table 7: The weighted supermatrix of factors affecting the employees' productivity from the studied managers' viewpoints|
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|Table 8: The limit supermatrix of factors affecting the employees' productivity from the studied managers' viewpoints|
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According to the results obtained from the limit matrix, the “leadership and management styles” (RW = 0.274) and “environmental factors” (RW = 0.176) were the most important and the least important clusters affecting the employees' productivity, respectively. Furthermore, “involving employees in the decision-making processes” (L1) (RW = 0.102) and “delegation of authority to the employees” (L2) (RW = 0.100) among all the studied factors were, respectively, the most important factors affecting the employees' productivity. However, “the existence of appropriate working and training facilities and equipment in the workplace” (E2) (RW < 0.001) had the lowest relative weight (RW) and was known as the least important factor affecting the employees' productivity [Table 8] and [Table 9].
|Table 9: The relative weights and priorities of clusters and elements (factors) affecting the employees' productivity from the studied managers' viewpoints|
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Moreover, the RW and the priority of each element (factor) affecting the employees' productivity were identified [Table 9]. The results showed that “the clarity of employees' roles and objectives” (P2) (RW = 0.292) in the cluster of job and motivational factors, “involving employees in the decision-making processes” (L1) (RW = 0.372) in the cluster of leadership and management styles, “employees' attitude toward the organization” (I1) (RW = 0.318) in the cluster of personal factors, and “the existence of appropriate opportunities for creativity in the workplace”(E3) (RW = 0.536) in the cluster of environmental factors had the highest RWs and were the most important factors in their clusters.
| Discussion|| |
Human resources are one of the most important strategic resources in the organizations, and the increase in the employees' productivity is one of the priorities of each organization's progress and development. This study aimed to identify and prioritize factors affecting the hospital employees' productivity from the viewpoint of all hospital managers working in the teaching hospitals affiliated to Iran, Shiraz University of Medical Sciences, in 2017.
According to the results of previous studies and literature review, 15 factors affecting employees' productivity were determined and classified into four clusters of job and motivational factors, leadership and management styles, personal factors, and environmental factors.
The results obtained from DEMATEL technique showed that “employees' attitude toward the organization” was the most important factor affecting the employees' productivity. In other words, “employees' attitude toward the organization” was the most affecting factor among all the studied factors, which is confirmed by the results of Kiani and Radfar, Susanty and Miradipta, and Abraham  studies.
In addition, “employees' attitude toward the organization” was the most affected factor among all the studied factors, which is consistent with the results of Kafash et al. and Winter and Sarros.
Also, the results of ANP technique showed that “leadership and management styles” was the most important cluster affecting the employees' productivity, which is similar to the results of Kavita, Babatunde and Emem, Iqbal et al., Butt et al., Bordbar, Allahverdi et al., and Bertrand and Schoar. The role and importance of management in the organizations is obvious. The skilled and effective managers are the pulse of the organizations and are considered to be the failure or success factor of an organization's programs. In general, managers have the authority to allocate the available resources, take decisions on promotions, assess the performance, etc., which may have effects on their employees. Therefore, managers can deeply affect their employees and have the ability to improve their productivity. It can be said that one of the most important managerial functions is to supervise the employees' performance in order to increase their productivity. Consequently, the role of management should not be ignored in the successful implementation of a human resource productivity improvement program in the health sector.
Moreover, in the leadership and management styles' cluster, the “involving employees in the decision-making processes” and “delegation of authority to the employees” were the most important factors affecting the employees' productivity, respectively, which are consistent with the findings of Thomas et al., Al-Jammal et al., and Meyerson and Dewettinck.
The management of today's large and modern organizations with a variety of activities and issues seems impossible without the delegation of authority. In such circumstances, top-level managers will have to delegate some of their authorities to their employees in order to have enough time to manage their core tasks. In other words, delegation of authority is an important aspect of management and it is essential for all managers to create an appropriate balance between their involvement in activities and duties, information processing, decision-making and problem-solving endeavors, and that of their employees in order to improve their productivity and achieve their organizational goals. On the other hand, it can result in employees' higher empowerment, commitment to their job and organization, self-confidence, job satisfaction, and productivity.,
Furthermore, the management theorists believe that employees' participation and involvement in decision-making processes allow them to influence their work and the conditions under which they work, can meet their higher level needs, including self-actualization, esteem, social belonging, and independence, and can improve their satisfaction and morale. They believe that, when the employees have a sense of partnership or being consulted, their secondary needs are met and they will work more than ever. Participation will affect the characteristics of relationships between employees and managers and will lead to a sense of value, a sense of having shared goals, greater cooperation, reduced absenteeism, enhanced work attitudes, higher individual work performance, decreased turnover, improved organizational learning culture, etc., among the employees. On the other hand, if the employees do not take part in the decision-making processes, the implementation of decisions taken by top managers can be difficult, especially when the decisions seem to be unfavorable.,,
Furthermore, the results of ANP technique showed that “environmental factors” was the least important cluster in which the “the existence of appropriate working and training facilities and equipment in the workplace” and “the existence of intimacy and cooperation in the workplace” were the least important factors affecting the employees' productivity, which are confirmed by the results of Abachi, Bordbar, Mohebbi et al., Talebbeydokhti et al., Bordbar, Allahverdi et al., and Tavari et al.
| Conclusion|| |
The results showed that the cluster of “leadership and management styles” and its factors, especially the “involving employees in the decision-making processes” and “delegation of authority to the employees,” were the most important factors affecting the employees' productivity from the viewpoint of the studied hospital managers. Therefore, adopting an appropriate leadership style and providing participatory management, involving the employees in the hospital decision-making processes, and delegating authority to the lower levels of the organization have significant effects on the increases in the employees' motivation and productivity.
The present article was extracted from a research project and was financially supported by Shiraz University of Medical Sciences (grant no. 95-01-68-12945). The researchers would like to thank the studied hospitals' managers for their kind cooperation with the researchers in collecting and analyzing data.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Rana A. Common Factors in Productive Firms: Lessons from Four Case Studies. Centre for Management and Economic Research, Lahore University of Management Sciences, CMER Working Paper Series, Working Paper No; 1997. p. 12-97.
Appelbaum SH, Adam J, Javeri N, Lessard M, Lion JP, Simard M, et al
. A case study analysis of the impact of satisfaction and organizational citizenship on productivity. Manag Res News 2005;28:1-26.
Jones DC, Kauhanen A. Human resource management policies and productivity: New evidence from an econometric case study. Oxf Rev Econ Policy 2006;22:38-526.
Hatami H, MirJafari A, Mojahedi Jahromi S. Investigation into the relationship of working life quality to organizational commitment and productivity in Jahrom medical science university. Q J New Approaches Educ Adm 2012;2:25-39.
Bordbar G. The effective factors on labor productivity with multi-criteria decision making techniques a case study: Personnel of Shahid Sadoghi Hospital in Yazd. J Health Adm 2013;16:70-83.
Tavari M, Soukhakian M, Mirnezhad SA. Identifying and prioritizing factors that affect human resource productivity by using MADM techniques. J Ind Manag 2009;1:71-88.
Allahverdi M, Farahabadi E, Sajadi H. Prioritizing factors effecting on human resources productivity: Viewing of middle class managers in Isfahan University of Medical Sciences-2009. Hospital 2011;9:77-85.
Alaolmaleki M, Yousefi B. Cognition & Compare of the Ways that Increase Human Resource Productivity in Semnan University of Medical Sciences. First Conference on Resource Management of Hospital. Tehran; 2002.
Spence H. The impact of workplace impowerment organizational trust on staff nurses work satisfaction and organizational commitment. J Health Manag 2002;4:56-85.
Bahadori MT, Ameriun A, Ravangard R, Abasi A, Jalalian M. Evaluation of input Indicators related to human resource productivity in a Military Hospital in Iran. Health Med 2010;4:7-323.
Roberts PM, Le Dorze G. Semantic organization, strategy use, and productivity in bilingual semantic verbal fluency. Brain Lang 1997;59:412-49.
Farhadi F, Ravangard R, Sajjadnia Z, Jafari A, Ghasemi H, Rahgoshay I. Study of factors affecting the productivity of nurses based on the ACHIEVE model and prioritizing them using analytic hierarchy process (AHP) technique, 2012. Arch Pharm Pract 2013;4:63-70.
Kiani N, Radfar R. Identifying and ranking factors effective on organizational productivity by DEMATEL model. Q J Productivity Manag 2015;9:111-30.
Roger M. Pulling through with productivity. J Transp Distrib 1996;36:26-39.
Ellis S, Dick P. Introduction to Organizational Behavior. 3rd
ed. London: McGraw-Hill; 2006.
Ravangard R, Yasami S, Shokrpour N, Sajjadnia Z, Farhadi P. The effects of supervisors' support and mediating factors on the nurses' job performance using structural equation modeling: A Case study. Health Care Manag (Frederick) 2015;34:265-76.
Ravangard R, Sajjadnia Z, Ansarizade N. Study of the effects of perceived organizational justice and its components on organizational commitment of administrative and financial employees of Shiraz University of Medical Sciences general hospitals in 2012. Arch Pharm Pract 2013;35:43-4.
Anbari Z, Sadageani A, Tabibi J. A comparative study of productivity mechanism in supporting services at Arak hospitals: Designing a model. J Zanjan Univ Med Sci 2005;13:49-56.
Cascio WF. Managing Human Resources: Productivity, Quality of Life, Profits. 7th
ed. Boston: McGraw-Hill/Irwin; 2006.
Dean BB, Crawley JA, Schmitt CM, Ofman JJ. The association between worker productivity and quality of life in GERD. Am J Gastroenterol 2001;96:S276-7.
Saaty TL. Fundamentals of the analytic network process – Dependence and feedback in decision-making with a single network. J Syst Sci Syst Eng 2004;13:129-57.
Wanga L, Chua J, Wub J. Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process. Int J Prod Econ 2007;107:151-61.
Tzeng GH, Chiang CH, Li CW. Evaluation intertwined effects in e-learning programs: A novel hybrid MCDM model based on factor analysis and DEMATEL. Expert Syst Appl 2007;32:1028-44.
Fontela E, Gabus A. The DEMATEL Observer, DEMATEL 1976 Report; 1976.
Ali SAM, Sorooshian S, Kie CJ. Modelling for Causal Interrelationships by DEMATEL. Contemp Eng Sci 2016;9:403-12.
Malekzadeh G, Kazemi M, Lagzian M, Mortazavi S. Modeling organizational intelligence using DEMATEL method in Iranian public universities. J Model Manag 2016;11:134-53.
Bahadori M, Ravangard R. Determining and prioritizing the organizational determinants of emergency medical services (EMS) in Iran. Iran Red Crescent Med J 2013;15:307-11.
Hu YC, Chiu YJ, Hsu CS, Chang YY. Identifying key factors for introducing GPS-based fleet management systems to the logistics industry. Math Probl Eng 2015;2015:1-14.
Wang J, Xing R. Decision Making with the Analytic Network Process: Economic, Political, Social and Technological Applications with Benefits, Opportunities, Costs and Risks. 2nd
ed. New York: Springer Science+Business Media, LLC; 2013.
Nilashi M, Ahmadi H, Ahani A, Ravangard R, Ibrahim Ob. Determining the importance of Hospital Information System adoption factors using Fuzzy Analytic Network Process (ANP). Technol Forecast Soc Change 2016;111:244-64.
Koushki MS, Akbari Sari A, Arab M, Ahmadi Engali K. Quality of working life and its relation with productivity of nurses' performance in Shahid Beheshti University of Medical Sciences hospitals. J Sch Public Health Inst Public Health Res 2013;10:81-90.
Susanty A, Miradipta R. Employee's job performance: The effect of attitude toward works, organizational commitment, and job satisfaction. J Teknik Ind 2013;15:13-24.
Abraham R. Organizational cynicism: Bases and consequences. Genet Soc Gen Psychol Monogr 2000;126:269-92.
Haghighi Kafash M, Mazloomi N, Mirzamohammadi F. Cuses and consequences of organizational cynicim (Case Study: Employees of Parsian Electronic Commerce Company). J Manag Stud Dev Eval 2011;21:117-39.
Winter R, Sarros J. Corporate reforms to Australian universities: Views from the academic hertlan. J Inst Res 2002;11:92-104.
Kavita S. Leadership style and employee productivity: A case study of Indian banking organizations. J Knowl Global 2015;8:39-67.
Babatunde O, Emem I. The impact of leadership style on employee's performance in an organization. Public Policy Adm Res 2015;5:193-205.
Iqbal N, Anwar S, Haider N. Effect of leadership style on employee performance. Arabian J Bus Manag Rev 2015;5:146-51.
Butt FS, Waseem M, Rafiq T, Nawab S, Khilji BA. The impact of leadership on the productivity of employees: An evidence from Pakistan. Res J Appl Sci Eng Technol 2014;7:5221-6.
Bertrand M, Schoar A. Managing with style: The effect of managers on firm policies. Q J Econ 2003;118:1169-208.
Thomas OO, Idowu OO, Olarewaju AA. Delegation of authority and employee performance: An empirical evidence from Ikeja division in Lagos State. J Entrep Innov 2016;8:103-10.
Al-Jammal HR, Al-Khasawneh AL, Hamadat MH. The impact of the delegation of authority on employees' performance at great Irbid municipality: Case study. Int J Hum Resour Stud 2015;5:48-69.
Meyerson G, Dewettinck B. Effect of empowerment on employees performance. Adv Res Econ Manag Sci 2012;2:40-6.
Hatami H. A study of the effect of delegation of authority with productivity of human resources in first region of Islamic Azad university. Q J New Approach Educ Adm 2013;3:51-6.
Bhatti KK, Qureshi TM. Impact of employee participation on job satisfaction, employee commitment and employee productivity. Int Rev Bus Res Pap 2007;3:54-68.
Shaed MM, Ishak S, Ramli Z. Employees' participation in decision making (PDM): A literature survey. Geografia Malays J Soc Space 2015;11:142-55.
Taleghani GR, Tanaomi MM, Farhangi A, Zarrinnegar MJ. Studying factors affect on increase of productivity (case study: Saman bank). J Public Adm 2011;3:115-30.
Abdulai IA, Shafiwu AB. Participatory decision making and employee productivity. A case study of community banks in the upper East region of Ghana. Bus Econ J 2014;5:10-9.
Abachi A. Investigation and Prioritize the effective factors on increasing the human resources productivity in agriculture bank using multi- attribute decision making model. Mod Appl Sci 2016;10:21-31.
Mohebbi F, Molavi Bistooni S, Bardi MH, Bolooki A. Evaluation of critical factors affecting HR productivity. J Appl Environ 2015;5:536-42.
Talebbeydokhti A, Mozafari Khorgo A, Rezaeizade A. Effective factors in humane resource productivity using MADM techniques in regional electric company in Ilam. Indian J Fundamental Appl Life Sci 2015;5:3978-88.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8], [Table 9]